process_raw_data

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of disclosing behavior. It mentions the read-normalize-deduplicate-upsert flow and the validation gate, but does not explain the side effects of upserting (e.g., overwriting existing records), permissions required, idempotency, or failure behavior. This leaves meaningful gaps for a mutating operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences plus a note, front-loaded with the core action and resource. Every sentence earns its place: the first states the operation, the second provides a critical default and prerequisite. No fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is complete for a batch-ingestion tool: it names inputs, outputs, and workflow order. The output schema exists, so return-value documentation is not required. The only missing context is around operational safety (e.g., reversibility, potential data loss) and error handling, but these are not essential for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all four parameters. The description adds only mild context (e.g., that `source` is a scraper name and that upsert happens), but does not materially enhance parameter understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reads validated raw records, normalizes, deduplicates, and upserts them into a specific collection (ContestHopperDb). It names the source table (CHRawdata.rawdata) and the target, distinguishing it from the many sibling tools that deal with validation or other processing steps.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to run get_records_for_validation + submit_raw_validation first, providing a clear prerequisite. It also notes the default behavior of only processing records with validationStatus='validated', which tells the agent when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.